Stereoscopic imaging, a technique whereby multiple imaging devices are used to form a three dimensional image through stereopsis, is becoming increasingly common in many fields. Stereoscopic imaging is particularly useful in robotics, where it is often desirable to gather three-dimensional information about a machine's environment. Stereoscopic imaging simulates the binocular visions of human eyes, which apply the principle of stereopsis to achieve depth perception. This technique can be reproduced by artificial imaging, devices by viewing a given object of interest using multiple imaging devices from slightly different vantage points. Differences between varying views of the object of interest convey depth information about the object's position, thereby enabling three-dimensional imaging of the object.
The ability of an imaging system per stereoscopic imaging to resolve depth is a function of a baseline, a distance between two imaging devices. The baseline limits the effective field-of-vision of the system for stereoscopic imaging in different ways. When the baseline is too small, for example, the imaging system cannot resolve distant objects. When the baseline is too large, the imaging system cannot see nearby objects (resulting in blind spots for the nearby objects). Additionally, when the baseline is too large, the overlap in the fields-of-vision of the two imaging devices is reduced, limiting the number of objects that can be viewed with depth perception. Furthermore, large, fixed baselines can take up large amounts of space and can be unwieldy. Thus, in most current systems for stereoscopic imaging, the baseline is fixed depending on whether imaging of nearby or far away objects is typically desired.
In view of the foregoing, there is a need for imaging systems and methods that support automatic baseline adjustment for stereoscopic imaging.